SMART FARMING AND LIVESTOCK ENTREPRENEURSHIP:

STRATEGIES FOR ENGAGING GRADUATE EMPLOYABILITY AND RURAL DEVELOPMENT IN NIGERIA

Abstract

This study investigates how technology-driven agricultural practices and livestock enterprise models influence graduate employability and rural economic development. Anchored on the Technology Acceptance Model (TAM) proposed by Fred Davis (1989), the research examines how perceived usefulness and ease of use of smart farming technologies shape graduates’ adoption behavior, skill acquisition, and entrepreneurial engagement. Specifically, the study examines the impact of smart farming technologies on graduate employability, evaluates the effectiveness of livestock entrepreneurship strategies in promoting sustainable rural development, and identifies key challenges constraining adoption. A mixed-methods approach combined quantitative surveys of 222 purposively and stratified randomly selected graduates, agribusiness operators, and key stakeholders with qualitative interviews and focus group discussions, providing a comprehensive understanding of measurable outcomes and lived experiences. Descriptive statistics, including means, standard deviations, and frequencies, alongside thematic qualitative analysis, were used to analyse the data. Findings indicate that smart farming adoption enhances graduate employability by improving technical skills, promoting self-employment, and expanding market access, although mentoring and institutional support remain inadequate. Livestock entrepreneurship strategies significantly improve rural income, community livelihoods, and value chain participation, but greater investment in capacity-building and training is needed. Key barriers include high technology costs, inadequate technical skills, limited market access, poor infrastructure, and low awareness. The study concludes that integrating smart farming and livestock entrepreneurship initiatives can substantially enhance graduate employability and rural development. It recommends strengthening mentoring and institutional support, expanding targeted training and extension services, and implementing integrated policy interventions to address structural and knowledge-based barriers.